Reducing illogical movements in the supply chain through mathematical optimisation with Mosel: The INEOS Inovyn case study
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- In today’s volatile industrial landscape, supply chain inefficiencies can no longer be overlooked. Among them, illogical movements remain a persistent challenge. These are unnecessary, costly transfers that do not add value to the supply chain. This thesis investigates such movements within the supply chain of INEOS Inovyn, where logistical choices are sometimes shaped by capacity limitations rather than optimal planning. To address this issue, a mathematical optimisation model was developed using the Xpress Mosel language. Grounded on real operational data from the Jemeppe-sur-Sambre production site, the model simulates cost-optimal distribution flows under various constraints. But a central question remains: would investing in additional internal storage capacity truly be economically viable? The findings offer not only a data-driven answer but also open the door to broader reflections on how companies can optimise their supply chains in a more sustainable way.